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  • Four Trends Shaping the Future of Analytics in Banking

    27 novembre 2024, par Daniel Crough — Banking and Financial Services

    While retail banking revenues have been growing in recent years, trends like rising financial crimes and capital required for generative AI and ML tech pose significant risks and increase operating costs across the financial industry, according to McKinsey’s State of Retail Banking report.

     

    Today’s financial institutions are focused on harnessing AI and advanced analytics to make their data work for them. To be up to the task, analytics solutions must allow banks to give consumers the convenient, personalised experiences they want while respecting their privacy.

     

    In this article, we’ll explore some of the big trends shaping the future of analytics in banking and finance. We’ll also look at how banks use data and technology to cut costs and personalise customer experiences.

    So, let’s get into it.

    Graph showing average age of IT applications in insurance (18 years)

    This doesn’t just represent a security risk, it also impacts the usability for both customers and employees. Does any of the following sound familiar ?

    • Only specific senior employees know how to navigate the software to generate custom reports or use its more advanced features.
    • Customer complaints about your site’s usability or online banking experience are routine.
    • Onboarding employees takes much longer than necessary because of convoluted systems.
    • Teams and departments experience ‘data siloing,’ meaning that not everyone can access the data they need.

    These are warning signs that IT systems are ready for a review. Anyone thinking, “If it’s not broken, why fix it ?” should consider that legacy systems can also present data security risks. As more countries introduce regulations to protect customer privacy, staying ahead of the curve is increasingly important to avoid penalties and litigation.

    And regulations aren’t the only trends impacting the future of financial institutions’ IT and analytics.

    4 trends shaping the future of analytics in banking

    New regulations and new technology have changed the landscape of analytics in banking.

    New privacy regulations impact banks globally

    The first major international example was the advent of GDPR, which went into effect in the EU in 2018. But a lot has happened since. New privacy regulations and restrictions around AI continue to roll out.

    • The European Artificial Intelligence Act (EU AI Act), which was held up as the world’s first comprehensive legislation on AI, took effect on 31 July 2024.
    • In Europe’s federated data initiative, Gaia-X’s planned cloud infrastructure will provide for more secure, transparent, and trustworthy data storage and processing.
    • The revised Payment Services Directive (PSD2) makes payments more secure and strengthens protections for European businesses and consumers, aiming to create a more integrated and efficient payments market.

    But even businesses that don’t have customers in Europe aren’t safe. Consumer privacy is a hot-button issue globally.

    For example, the California Consumer Privacy Act (CCPA), which took effect in January, impacts the financial services industry more than any other. Case in point, 34% of CCPA-related cases filed in 2022 were related to the financial sector.

    California’s privacy regulations were the first in the US, but other states are following closely behind. On 1 July 2024, new privacy laws went into effect in Florida, Oregon, and Texas, giving people more control over their data.

    Share of CCPA cases in the financial industry in 2022 (34%)

    One typical issue for companies in the banking industry is that their privacy measures regarding user data collected from their website are much less lax than those in their online banking system.

    It’s better to proactively invest in a privacy-centric analytics platform before you get tangled up in a lawsuit and have to pay a fine (and are forced to change your system anyway). 

    And regulatory compliance isn’t the only bonus of an ethical analytics solution. The right alternative can unlock key customer insights that can help you improve the user experience.

    The demand for personalised banking services

    At the same time, consumers are expecting a more and more streamlined personal experience from financial institutions. 86% of bank employees say personalisation is a clear priority for the company. But 63% described resources as limited or only available after demonstrating clear business cases.

    McKinsey’s The data and analytics edge in corporate and commercial banking points out how advanced analytics are empowering frontline bank employees to give customers more personalised experiences at every stage :

    • Pre-meeting/meeting prep : Using advanced analytics to assess customer potential, recommend products, and identify prospects who are most likely to convert
    • Meetings/negotiation : Applying advanced models to support price negotiations, what-if scenarios and price multiple products simultaneously
    • Post-meeting/tracking : Using advanced models to identify behaviours that lead to high performance and improve forecast accuracy and sales execution

    Today’s banks must deliver the personalisation that drives customer satisfaction and engagement to outperform their competitors.

    The rise of AI and its role in banking

    With AI and machine learning technologies becoming more powerful and accessible, financial institutions around the world are already reaping the rewards.

    McKinsey estimates that AI in banking could add $200 to 340 billion annually across the global banking sector through productivity gains.

    • Credit card fraud prevention : Algorithms analyse usage to flag and block fraudulent transactions.
    • More accurate forecasting : AI-based tools can analyse a broader spectrum of data points and forecast more accurately.
    • Better risk assessment and modelling : More advanced analytics and predictive models help avoid extending credit to high-risk customers.
    • Predictive analytics : Help spot clients most likely to churn 
    • Gen-AI assistants : Instantly analyse customer profiles and apply predictive models to suggest the next best actions.

    Considering these market trends, let’s discuss how you can move your bank into the future.

    Using analytics to minimise risk and establish a competitive edge 

    With the right approach, you can leverage analytics and AI to help future-proof your bank against changing customer expectations, increased fraud, and new regulations.

    Use machine learning to prevent fraud

    Every year, more consumers are victims of credit and debit card fraud. Debit card skimming cases nearly doubled in the US in 2023. The last thing you want as a bank is to put your customer in a situation where a criminal has spent their money.

    This not only leads to a horrible customer experience but also creates a lot of internal work and additional costs.Thankfully, machine learning can help identify suspicious activity and stop transactions before they go through. For example, Mastercard’s fraud prevention model has improved fraud detection rates by 20–300%.

    A credit card fraud detection robot

    Implementing a solution like this (or partnering with credit card companies who use it) may be a way to reduce risk and improve customer trust.

    Foresee and avoid future issues with AI-powered risk management

    Regardless of what type of financial products organisations offer, AI can be an enormous tool. Here are just a few ways in which it can mitigate financial risk in the future :

    • Predictive analytics can evaluate risk exposure and allow for more informed decisions about whether to approve commercial loan applications.
    • With better credit risk modelling, banks can avoid extending personal loans to customers most likely to default.
    • Investment banks (or individual traders or financial analysts) can use AI- and ML-based systems to monitor market and trading activity more effectively.

    Those are just a few examples that barely scratch the surface. Many other AI-based applications and analytics use cases exist across all industries and market segments.

    Protect customer privacy while still getting detailed analytics

    New regulations and increasing consumer privacy concerns don’t mean banks and financial institutions should forego website analytics altogether. Its insights into performance and customer behaviour are simply too valuable. And without customer interaction data, you’ll only know something’s wrong if someone complains.

    Fortunately, it doesn’t have to be one or the other. The right financial analytics solution can give you the data and insights needed without compromising privacy while complying with regulations like GDPR and CCPA.

    That way, you can track usage patterns and improve site performance and content quality based on accurate data — without compromising privacy. Reliable, precise analytics are crucial for any bank that’s serious about user experience.

    Use A/B testing and other tools to improve digital customer experiences

    Personalised digital experiences can be key differentiators in banking and finance when done well. But there’s stiff competition. In 2023, 40% of bank customers rated their bank’s online and mobile experience as excellent. 

    Improving digital experiences for users while respecting their privacy means going above and beyond a basic web analytics tool like Google Analytics. Invest in a platform with features like A/B tests and user session analysis for deeper insights into user behaviour.

    Diagram of an A/B test with 4 visitors divided into two groups shown different options

    Behavioural analytics are crucial to understanding customer interactions. By identifying points of friction and drop-off points, you can make digital experiences smoother and more engaging.

    Matomo offers all this and is a great GDPR-compliant alternative to Google Analytics for banks and financial institutions

    Of course, this can be challenging. This is why taking an ethical and privacy-centric approach to analytics can be a key competitive edge for banks. Prioritising data security and privacy will attract other like-minded, ethically conscious consumers and boost customer loyalty.

    Get privacy-friendly web analytics suitable for banking & finance with Matomo

    Improving digital experiences for today’s customers requires a solid web analytics platform that prioritises data privacy and accurate analytics. And choosing the wrong one could even mean ending up in legal trouble or scrambling to reconstruct your entire analytics setup.

    Matomo provides privacy-friendly analytics with 100% data accuracy (no sampling), advanced privacy controls and the ability to run A/B tests and user session analysis within the same platform (limiting risk and minimising costs). 

    It’s easy to get started with Matomo. Users can access clear, easy-to-understand metrics and plenty of pre-made reports that deliver valuable insights from day one. Form usage reports can help banks and fintechs identify potential issues with broken links or technical glitches and reveal clues on improving UX in the short term.

    Over one million websites, including some of the world’s top banks and financial institutions, use Matomo for their analytics.

    Start your 21-day free trial to see why, or book a demo with one of our analytics experts.

  • Data Privacy Regulations : Essential Knowledge for Global Business

    6 mars, par Daniel Crough

    If you run a website that collects visitors’ data, you might be violating privacy regulations somewhere in the world. At last count, over 160 countries have privacy laws — and your customers in those countries know about them.

    A recent survey found that 53% of people who answered know about privacy rules in their country and want to follow them. This is up from 46% two years ago. Furthermore, customers increasingly want to buy from businesses they can trust with their data.

    That’s why businesses must take data privacy seriously. In this article, we’ll first examine data privacy rules, why we need them, and how they are enforced worldwide. Finally, we’ll explore strategies to ensure compliance and tools that can help.

    What are data privacy regulations ?

    Let’s first consider data privacy. What is it ? The short answer is individuals’ ability to control their personal information. That’s why we need laws and rules to let people decide how their data is collected, used, and shared. Crucially, the laws empower individuals to withdraw permission to use their data anytime.

    The UNCTAD reports that only 13 countries had data protection laws or rules before the 2000s. Many existed before businesses could offer online services, so they needed updating. Today, 162 national laws protect data privacy, half of which emerged in the last decade.

    Why is this regulation necessary ?

    There are many reasons, but the impetus comes from consumers who want their governments to protect their data from exploitation. They understand that participating in the digital economy means sharing personal information like email addresses and telephone numbers, but they want to minimise the risks of doing so.

    Data privacy regulation is essential for :

    • Protecting personal information from exploitation with transparent rules and guidelines on handling it securely.
    • Implementing adequate security measures to prevent data breaches.
    • Enforcing accountability for how data is collected, stored and processed.
    • Giving consumers control over their data.
    • Controlling the flow of data across international borders in a way that fully complies with the regulations.
    • Penalising companies that violate privacy laws.

    Isn’t it just needless red tape ?

    Data breaches in recent years have been one of the biggest instigators of the increase in data privacy regulations. A list of the top ten data breaches illustrates the point.

    #CompanyLocationYear# of RecordsData Type
    1YahooGlobal20133Buser account information
    2AadhaarIndia20181.1Bcitizens’ ID/biometric data
    2AlibabaChina20191.1Busers’ personal data
    4LinkedInGlobal2021700Musers’ personal data
    5Sina WeiboChina2020538Musers’ personal data
    6FacebookGlobal2019533Musers’ personal data
    7Marriott Int’lGlobal2018500Mcustomers’ personal data
    8YahooGlobal2014500Muser account information
    9Adult Friend FinderGlobal2016412.2Muser account information
    10MySpaceUSA2013360Muser account information

    And that’s just the tip of the iceberg. Between November 2005 and November 2015, the US-based Identity Theft Resource Center counted 5,754 data breaches that exposed 856,548,312 records, mainly in that country.

    It’s no wonder that citizens worldwide want organisations they share their personal data with to protect that data as if it were their own. More specifically, they want their governments to :

    • Protect their consumer rights
    • Prevent identity theft and other consumer fraud
    • Build trust between consumers and businesses
    • Improve cybersecurity measures
    • Promote ethical business practices
    • Uphold international standards

    Organisations using personal data in their operations want to minimise financial and reputational risk. That’s common sense, especially when external attacks cause 68% of data breaches.

    The terminology of data privacy

    With 162 national laws already in place, the legal space surrounding data privacy grows more complex every day. Michalsons has a list of different privacy laws and regulations in force in significant markets around the world.

    Fortunately, there’s plenty of commonality for two reasons : first, all countries want to solve the same problem ; second, those drafting the legislation have adopted much of what other countries have already developed. As a result, the terminology remains almost the same, even when the language changes.

    These are the core concepts at play :

    TermDefinition
    Access and controlConsumers can access, review, edit and delete their data
    Data protectionOrganisations must protect data from being stolen or compromised
    Consumer consentConsumers can grant and withdraw or refuse access to their data
    DeletionConsumers can request to have their data erased
    Data breachWhen the security of data has been compromised
    Data governanceThe management of data within an organisation
    Double opt-inTwo-factor authentication to add a layer of confirmation
    GDPRGoverning data privacy in Europe since 2016
    Personally identifiable information (PII)Data used to identify, locate, or contact an individual
    PseudonymisationReplace personal identifiers with artificial identifiers or pseudonyms
    Publicly available informationData from official sources, without restrictions on access or use
    RectificationConsumers can request to have errors in their data corrected

    Overview of current data privacy legislation

    Over three-quarters of the world has formulated and rolled out data privacy legislation — or is currently doing so. Here’s a breakdown of the laws and regulations you can expect to find in most significant markets worldwide.

    Europe

    Thoughts of protecting data privacy first occurred in Europe when the German government became concerned about automated data processing in 1970. A few years later, Sweden was the first country to enact a law requiring permits for processing personal data, establishing the first data protection authority.

    General Data Protection Regulation (GDPR)

    Sweden’s efforts triggered a succession of European laws and regulations that culminated in the European Union (EU) GDPR, enacted in 2016 and enforced from 25 May 2018. It’s a detailed and comprehensive privacy law that safeguards the personal data and privacy of EU citizens.

    The main objectives of GDPR are :

    • Strengthening the privacy rights of individuals by empowering them to control their data.
    • Establishing a uniform data framework for data privacy across the EU.
    • Improving transparency and accountability by mandating businesses to handle personal data responsibly and fully disclose how they use it.
    • Extending the regulation’s reach to organisations external to the EU that collect, store and process the data of EU residents.
    • Requiring organisations to conduct Protection Impact Assessments (PIAs) for “high-risk” projects.

    ePrivacy Regulation on Privacy and Electronic Communications (PECR)

    The second pillar of the EU’s strategy to regulate the personal data of its citizens is the ePrivacy Regulation on Privacy and Electronic Communications (EU PECR). Together with the GDPR, it will comprise data protection law in the union. This regulation applies to :

    • Providers of messaging services like WhatsApp, Facebook and Skype
    • Website owners
    • Owners of apps that have electronic communication components
    • Commercial direct marketers
    • Political parties sending promotional messages electronically
    • Telecommunications companies
    • ISPs and WiFi connection providers

    The EU PECR was intended to commence with GDPR on 25 May 2018. That didn’t happen, and as of January 2025, it was in the process of being redrafted.

    EU Data Act

    One class of data isn’t covered by GDPR or PECR : internet product-generated data. The EU Data Act provides the regulatory framework to govern this data, and it applies to manufacturers, suppliers, and users of IoT devices or related services.

    The intention is to facilitate data sharing, use, and reuse and to facilitate organisations’ switching to a different cloud service provider. The EU Data Act entered into force on 11 January 2024 and is applicable from September 2025.

    GDPR UK

    Before Brexit, the EU GDPR was in force in the UK. After Brexit in 2020, the UK opted to retain the regulations as UK GDPR but asserted independence to keep the framework under review. It’s part of a wider package of reform to the data protection environment that includes the Data Protection Act 2018 and the UK PECR.

    In the USA

    The primary federal law regarding data privacy in the US is the Privacy Act of 1974, which has been in revision for some time. However, rather than wait for the outcome of that process, many business sectors and states have implemented their own measures.

    Sector-specific data protection laws

    This sectoral approach to data protection relies on a combination of legislation, regulation and self-regulation rather than governmental control. Since the mid-1990s, the country has allowed the private sector to lead on data protection, resulting in ad hoc legislation arising when circumstances require it. Examples include the Video Privacy Protection Act of 1988, the Cable Television Protection and Competition Act of 1992 and the Fair Credit Reporting Act.

    Map showing states with data privacy regulation and states planning it

    California Consumer Privacy Act (CCPA)

    California was the first state to act when federal privacy law development stalled. In 2018, it enacted the California Consumer Privacy Act (CCPA) to protect and enforce Californians’ rights regarding the privacy of their personal information. It came into force in 2020.

    California Privacy Act (CPRA)

    In November of that same year, California voters approved the California Privacy Rights Act (CPRA). Billed as the strongest consumer privacy law ever enacted in the US, CPRA works with CCPA and adds the best elements of laws and regulations in other jurisdictions (Europe, Japan, Israel, New Zealand, Canada, etc.) into California’s personal data protection regime.

    Virginia Consumer Data Protection Act (CDPA)

    In March 2021, Virginia became the next US state to implement privacy legislation. The Virginia Consumer Data Protection Act (VCDPA), which is also informed by global legislative developments, tries to strike a balance between consumer privacy protections and business interests. It governs how businesses collect, use, and share consumer data.

    Colorado Privacy Act (CPA)

    Developed around the same time as VCDPA, the Colorado Privacy Act (CPA) was informed by that law and GDPR and CCPA. Signed into law in July 2021, the CPA gives Colorado residents more control over their data and establishes guidelines for businesses on handling the data.

    Other states generally

    Soon after, additional states followed suit and, similar to Colorado, examined existing legislation to inform the development of their own data privacy laws and regulations. At the time of writing, the states with data privacy laws at various stages of development were Connecticut, Florida, Indiana, Iowa, Montana, New York, Oregon, Tennessee, Texas, and Utah.

    By the time you read this article, more states may be doing it, and the efforts of some may have led to laws and regulations coming into force. If you’re already doing business or planning to do business in the US, you should do your own research on the home states of your customers.

    Globally

    Beyond Europe and the US, other countries are also implementing privacy regulations. Some were well ahead of the trend. For example, Chile’s Law on the Protection of Private Life was put on the books in 1999, while Mauritius enacted its first Data Protection Act in 2004 — a second one came along in 2017 to replace it.

    Canada

    The regulatory landscape around data privacy in Canada is as complicated as it is in the US. At a federal government level, there are two laws : The Privacy Act for public sector institutions and the Personal Information Protection and Electronic Documents Act (PIPEDA) for the private sector.

    PIPEDA is the one to consider here. Like all other data privacy policies, it provides a framework for organisations handling consumers’ personal data in Canada. Although not quite up to GDPR standard, there are moves afoot to close that gap.

    The Digital Charter Implementation Act, 2022 (aka Bill C-27) is proposed legislation introduced by federal agencies in June 2022. It’s intended to align Canada’s privacy framework with global standards, such as GDPR, and address emerging digital economy challenges. It may or may not have been finalised when you read this.

    At the provincial level, three of Canada’s provinces—Alberta, British Columbia, and Quebec—have introduced laws and regulations of their own. Their rationale was similar to that of Bill C-27, so they may become redundant if and when that bill passes.

    Japan

    Until recently, Japan’s Act on the Protection of Personal Information (APPI) was considered by many to be the most comprehensive data protection law in Asia. Initially introduced in 2003, it was significantly amended in 2020 to align with global privacy standards, such as GDPR.

    APPI sets out unambiguous rules for how businesses and organisations collect, use, and protect personal information. It also sets conditions for transferring the personal information of Japanese residents outside of Japan.

    Map showing countries with legislation and draft legislation and those without any at all.

    China

    The new, at least for now, most comprehensive data privacy law in Asia is China’s Personal Information Protection Law (PIPL). It’s part of the country’s rapidly evolving data governance framework, alongside the Cybersecurity Law and the Data Security Law.

    PIPL came into effect in November 2021 and was informed by GDPR and Japan’s APPI, among others. The data protection regime establishes a framework for protecting personal information and imposes significant compliance obligations on businesses operating in China or targeting consumers in that country.

    Other countries

    Many other nations have already brought in legislation and regulations or are in the process of developing them. As mentioned earlier, there are 162 of them at this point, and they include :

    ArgentinaCosta RicaParaguay
    AustraliaEcuadorPeru
    BahrainHong KongSaudi Arabia
    BermudaIsraelSingapore
    BrazilMauritiusSouth Africa
    ChileMexicoUAE
    ColombiaNew ZealandUruguay

    Observant readers might have noticed that only two countries in Africa are on that list. More than half of the 55 countries on the continent have or are working on data privacy legislation.

    It’s a complex landscape

    Building a globalised business model has become very complicated, with so much legislation already in play and more coming. What you must do depends on the countries you plan to operate in or target. And that’s before you consider the agreements groups of countries have entered into to ease the flow of personal data between them.

    In this regard, the EU-US relationship is instructive. When GDPR came into force in 2016, so did the EU-US Privacy Shield. However, about four years later, the Court of Justice of the European Union (CJEU) invalidated it. The court ruled that the Privacy Shield didn’t adequately protect personal data transferred from the EU to the US.

    The ruling was based on US laws that allow excessive government surveillance of personal data transferred to the US. The CJEU found that this conflicted with the basic rights of EU citizens under the European Union’s Charter of Fundamental Rights.

    A replacement was negotiated in a new mechanism : the EU-US Data Privacy Framework. However, legal challenges are expected, and its long-term viability is uncertain. The APEC Privacy Framework and the OECD Privacy Framework, both involving the US, also exist.

    The EU-US Privacy Shield regulates transfer of personal data between the EU and the US

    Penalties for non-compliance

    Whichever way you look at it, consumer data privacy laws and regulations make sense. But what’s really interesting is that many of them have real teeth to punish offenders. GDPR is a great example. It was largely an EU concern until January 2022 when the French data protection regulator hit Google and Facebook with serious fines and criminal penalties.

    Google was fined €150M, and Facebook was told to pay €60M for failing to allow French users to reject cookie tracking technology easily. That started a tsunami of ever-larger fines.

    The largest so far was the €1.2B fine levied by the Irish Data Protection Commission on Meta, the owner of Instagram, Facebook, and WhatsApp. It was issued for transferring European users’ personal data to the US without adequate data protection mechanisms. This significant penalty demonstrated the serious financial implications of non-compliance.

    These penalties follow a structured approach rather than arbitrary determinations. The GDPR defines an unambiguous framework for fines. They can be up to 4% of a company’s total global turnover in the previous fiscal year. That’s a serious business threat.

    What should you do ?

    For businesses committed to long-term success, accepting and adapting to regulatory requirements is essential. Data privacy regulations and protection impact assessments are here to stay, with many national governments implementing similar frameworks.

    However, there is some good news. As you’ve seen, many of these laws and regulations were informed by GDPR or retrospectively aligned. That’s a good place to start. Choose tools to handle your customer’s data that are natively GDPR-compliant.

    For example, web analytics is all about data, and a lot of that data is personal. And if, like many people, you use Google Analytics 4, you’re already in trouble because it’s not GDPR-compliant by default. And achieving compliance requires significant additional configuration.

    A better option would be to choose a web analytics platform that is compliant with GDPR right off the bat. Something like Matomo would do the trick. Then, complying with any of the tweaks individual countries have made to the basic GDPR framework will be a lot easier—and may even be handled for you.

    Privacy-centric data strategies

    Effective website data analysis is essential for business success. It enables organisations to understand customer needs and improve service delivery.

    But that data doesn’t necessarily need to be tied to their identity — and that’s at the root of many of these regulations.

    It’s not to stop companies from collecting data but to encourage and enforce responsible and ethical handling of that data. Without an official privacy policy or ethical data collection practices, the temptation for some to use and abuse that data for financial gain seems too great to resist.

    Cookie usage and compliance

    There was a time when cookies were the only way to collect reliable information about your customers and prospects. But under GDPR, and in many countries that based or aligned their laws with GDPR, businesses have to give users an easy way to opt out of all tracking, particularly tracking cookies.

    So, how do you collect the information you need without cookies ? Easy. You use a web analytics platform that doesn’t depend wholly on cookies. For example, in certain countries and when configured for maximum privacy, Matomo allows for cookieless operation. It can also help you manage the cookie consent requirements of various data privacy regulations.

    Choose the right tools

    Data privacy regulations have become a permanent feature of the global business landscape. As digital commerce continues to expand, these regulatory frameworks will only become more established. Fortunately, there is a practical approach forward.

    As mentioned several times, GDPR is considered by many countries to be a particularly good example of effective data privacy regulation. For that reason, many of them model their own legislation on the EU’s effort, making a few tweaks here and there to satisfy local requirements or anomalies.

    As a result, if you comply with GDPR, the chances are that you’ll also comply with many of the other data privacy regulations discussed here. That also means that you can select tools for your data harvesting and analytics that comply with the GDPR out of the box, so to speak. Tools like Matomo.

    Matomo lets website visitors retain full control over their data.

    Before deciding whether to go with Matomo On-premise or the EU-hosted cloud version, why not start your 21-day free trial ? No credit card required.

  • Making Your First-Party Data Work for You and Your Customers

    11 mars, par Alex Carmona

    At last count, 162 countries had enacted data privacy policies of one kind or another. These laws or regulations, without exception, intend to eliminate the use of third-party data. That puts marketing under pressure because third-party data has been the foundation of online marketing efforts since the dawn of the Internet.

    Marketers need to future-proof their operations by switching to first-party data. This will require considerable adjustment to systems and processes, but the reward will be effective marketing campaigns that satisfy privacy compliance requirements and bring the business closer to its customers.

    To do that, you’ll need a coherent first-party data strategy. That’s what this article is all about. We’ll explain the different types of personal data and discuss how to use them in marketing without compromising or breaching data privacy regulations. We’ll also discuss how to build that strategy in your business. 

    So, let’s dive in.

    The different data types

    There are four distinct types of personal data used in marketing, each subject to different data privacy regulations.

    Before getting into the different types, it’s essential to understand that all four may comprise one or more of the following :

    Identifying dataName, email address, phone number, etc.
    Behavioural dataWebsite activity, app usage, wishlist content, purchase history, etc.
    Transactional dataOrders, payments, subscription details, etc.
    Account dataCommunication preferences, product interests, wish lists, etc.
    Demographic dataAge, gender, income level, education, etc.
    Geographic DataLocation-based information, such as zip codes or regional preferences.
    Psychographic DataInterests, hobbies and lifestyle preferences.

    First-party data

    When businesses communicate directly with customers, any data they exchange is first-party. It doesn’t matter how the interaction occurs : on the telephone, a website, a chat session, or even in person.

    Of course, the parties involved aren’t necessarily individuals. They may be companies, but people within those businesses will probably share at least some of the data with colleagues. That’s fine, so long as the data : 

    • Remains confidential between the original two parties involved, and 
    • It is handled and stored following applicable data privacy regulations.

    The core characteristic of first-party data is that it’s collected directly from customer interactions. This makes it reliable, accurate and inherently compliant with privacy regulations — assuming the collecting party complies with data privacy laws.

    A great example of first-party data use is in banking. Data collected from customer interactions is used to provide personalised services, detect fraud, assess credit risk and improve customer retention.

    Zero-party data

    There’s also a subset of first-party data, sometimes called zero-party data. It’s what users intentionally and proactively share with a business. It can be preferences, intentions, personal information, survey responses, support tickets, etc.

    What makes it different is that the collection of this data depends heavily on the user’s trust. Transparency is a critical factor, too ; visitors expect to be informed about how you’ll use their data. Consumers also have the right to withdraw permission to use all or some of their information at any time.

    Diagram showing how a first-party data strategy is built on trust and transparency

    Second-party data

    This data is acquired from a separate organisation that collects it firsthand. Second-party data is someone else’s first-party data that’s later shared with or sold to other businesses. The key here is that whoever owns that data must give explicit consent and be informed of who businesses share their data with.

    A good example is the cooperation between hotel chains, car rental companies, and airlines. They share joint customers’ flight data, hotel reservations, and car rental bookings, much like travel agents did before the internet undermined that business model.

    Third-party data

    This type of data is the arch-enemy of lawmakers and regulators trying to protect the personal data of citizens and residents in their country. It’s information collected by entities that have no direct relationship with the individuals whose data it is.

    Third-party data is usually gathered, aggregated, and sold by data brokers or companies, often by using third-party cookies on popular websites. It’s an entire business model — these third-party brokers sell data for marketing, analytics, or research purposes. 

    Most of the time, third-party data subjects are unaware that their data has been gathered and sold. Hence the need for strong data privacy regulations.

    Benefits of a first-party data strategy

    First-party data is reliable, accurate, and ethically sourced. It’s an essential part of any modern digital marketing strategy.

    More personalised experiences

    The most important application of first-party data is customising and personalising customers’ interactions based on real behaviours and preferences. Personalised experiences aren’t restricted to websites and can extend to all customer communication.

    The result is company communications and marketing messages are far more relevant to customers. It allows businesses to engage more meaningfully with them, building trust and strengthening customer relationships. Inevitably, this also results in stronger customer loyalty and better customer retention.

    Greater understanding of customers

    Because first-party data is more accurate and reliable, it can be used to derive valuable insights into customer needs and wants. When all the disparate first-party data points are centralised and organised, it’s possible to uncover trends and patterns in customer behaviour that might not be apparent using other data.

    This helps businesses predict and respond to customer needs. It also allows marketing teams to be more deliberate when segmenting customers and prospects into like-minded groups. The data can also be used to create more precise personas for future campaigns or reveal how likely a customer would be to purchase in response to a campaign.

    Build trust with customers

    First-party data is unique to a business and originates from interactions with customers. It’s also data collected with consent and is “owned” by the company — if you can ever own someone else’s data. If treated like the precious resource, it can help businesses build trust with customers.

    However, developing that trust requires a transparent, step-by-step approach. This gradually strengthens relationships to the point where customers are more comfortable sharing the information they’re asked for.

    However, while building trust is a long and sometimes arduous process, it can be lost in an instant. That’s why first-party data must be protected like the Crown Jewels.

    Image showing the five key elements of a first-party data strategy

    Components of a first-party data strategy

    Security is essential to any first-party data strategy, and for good reason. As Gartner puts it, a business must find the optimal balance between business outcomes and data risk mitigation. Once security is baked in, attention can turn to the different aspects of the strategy.

    Data collection

    There are many ways to collect first-party data ethically, within the law and while complying with data privacy regulations, such as Europe’s General Data Protection Regulation (GDPR). Potential sources include :

    Website activityforms and surveys, behavioural tracking, cookies, tracking pixels and chatbots
    Mobile app interactionsin-app analytics, push notifications and in-app forms
    Email marketingnewsletter sign-ups, email engagement tracking, promotions, polls and surveys 
    Eventsregistrations, post-event surveys and virtual event analytics
    Social media interactionpolls and surveys, direct messages and social media analytics
    Previous transactionspurchase history, loyalty programmes and e-receipts 
    Customer service call centre data, live chat, chatbots and feedback forms
    In-person interactions in-store purchases, customer feedback and Wi-Fi sign-ins
    Gated contentwhitepapers, ebooks, podcasts, webinars and video downloads
    Interactive contentquizzes, assessments, calculators and free tools
    CRM platformscustomer profiles and sales data
    Consent managementprivacy policies, consent forms, preference setting

    Consent management

    It may be the final item on the list above, but it’s also a key requirement of many data privacy laws and regulations. For example, the GDPR is very clear about consent : “Processing personal data is generally prohibited, unless it is expressly allowed by law, or the data subject has consented to the processing.”

    For that reason, your first-party data strategy must incorporate various transparent consent mechanisms, such as cookie banners and opt-in forms. Crucially, you must provide customers with a mechanism to manage their preferences and revoke that consent easily if they wish to.

    Data management

    Effective first-party data management, mainly its security and storage, is critical. Most data privacy regimes restrict the transfer of personal data to other jurisdictions and even prohibit it in some instances. Many even specify where residents’ data must be stored.

    Consider this cautionary tale : The single biggest fine levied for data privacy infringement so far was €1.2 billion. The Irish Data Protection Commission imposed a massive fine on Meta for transferring EU users’ data to the US without adequate data protection mechanisms.

    Data security is critical. If first-party data is compromised, it becomes third-party data, and any customer trust developed with the business will evaporate. To add insult to injury, data regulators could come knocking. That’s why the trend is to use encryption and anonymisation techniques alongside standard access controls.

    Once security is assured, the focus is on data management. Many businesses use a Customer Data Platform. This software gathers, combines and manages data from many sources to create a complete and central customer profile. Modern CRM systems can also do that job. AI tools could help find patterns and study them. But the most important thing is to keep databases clean and well-organised to make it easier to use and avoid data silos.

    Data activation

    Once first-party data has been collected and analysed, it needs to be activated, which means a business needs to use it for the intended purpose. This is the implementation phase where a well-constructed first-party strategy pays off. 

    The activation stage is where businesses use the intelligence they gather to :

    • Personalise website and app experiences
    • Adapt marketing campaigns
    • Improve conversion rates
    • Match stated preferences
    • Cater to observed behaviours
    • Customise recommendations based on purchase history
    • Create segmented email campaigns
    • Improve retargeting efforts
    • Develop more impactful content

    Measurement and optimisation

    Because first-party data is collected directly from customers or prospects, it’s far more relevant, reliable, and specific. Your analytics and campaign tracking will be more accurate. This gives you direct and actionable insights into your audience’s behaviour, empowering you to optimise your strategies and achieve better results.

    The same goes for your collection and activation efforts. An advanced web analytics platform like Matomo lets you identify key user behaviour and optimise your tracking. Heatmaps, marketing attribution tools, user behaviour analytics and custom reports allow you to segment audiences for better traction (and collect even more first-party data).

    Image showing the five steps to developing a first-party data strategy

    How to build a first-party data strategy

    There are five important and sequential steps to building a first-party data strategy. But this isn’t a one-time process. It must be revisited regularly as operating and regulatory environments change. There are five steps : 

    1. Audit existing data

    Chances are that customers already freely provide a lot of first-party data in the normal course of business. The first step is to locate this data, and the easiest way to do that is by mapping the customer journey. This identifies all the touchpoints where first-party data might be found.

    1. Define objectives

    Then, it’s time to step back and figure out the goals of the first-party data strategy. Consider what you’re trying to achieve. For example :

    • Reduce churn 
    • Expand an existing loyalty programme
    • Unload excess inventory
    • Improve customer experiences

    Whatever the objectives are, they should be clear and measurable.

    1. Implement tools and technology

    The first two steps point to data gaps. Now, the focus turns to ethical web analytics with a tool like Matomo. 

    To further comply with data privacy regulations, it may also be appropriate to implement a Consent Management Platform (CMP) to help manage preferences and consent choices.

    1. Build trust with transparency

    With the tools in place, it’s time to engage customers. To build trust, keep them informed about how their data is used and remind them of their right to withdraw their consent. 

    Transparency is crucial in such engagement, as outlined in the 7 GDPR principles.

    1. Continuously improve

    Rinse and repeat. The one constant in business and life is change. As things change, they expose weaknesses or flaws in the logic behind systems and processes. That’s why a first-party data strategy needs to be continually reviewed, updated, and revised. It must adapt to changing trends, markets, regulations, etc. 

    Tools that can help

    Looking back at the different types of data, it’s clear that some are harder and more bothersome to get than others. But capturing behaviours and interactions can be easy — especially if you use tools that follow data privacy rules.

    But here’s a tip. Google Analytics 4 isn’t compliant by default, especially not with Europe’s GDPR. It may also struggle to comply with some of the newer data privacy regulations planned by different US states and other countries.

    Matomo Analytics is compliant with the GDPR and many other data privacy regulations worldwide. Because it’s open source, it can be integrated with any consent manager.

    Get started today by trying Matomo for free for 21 days,
    no credit card required.